LEADER 01659nam 2200361 n 450 001 996397717203316 005 20200824121442.0 035 $a(CKB)4940000000065237 035 $a(EEBO)2264219673 035 $a(UnM)99831148_35611e 035 $a(UnM)99831148_35611 035 $a(EXLCZ)994940000000065237 100 $a19950927d1692 uy | 101 0 $alat 135 $aurbn||||a|bb| 200 10$aLibrorum manuscriptorum in duabus insignibus bibliothecis$b[electronic resource] $ealtera Tenisoniana, Londini; altera Dugdaliana, Oxonii; catalogus. Edidit E.G 210 $aOxonii $ce. Theatro Sheldoniano: veneunt in officina T. Bennett, bipliopolę Londinensis$da.D. M.DC.XCII. [1692] 215 $a[8], 31, [5], 20 p 300 $aCaption title on p. 1: Catalogus librorum mss. in bibliotheca Tenisoniana, Londini. 300 $aDivisional title page on p. [2] (second sequence): Librorum manuscriptorum quos cl. Guil. Dugdalius ... . 300 $aReproduction of the original in the Bodleian Library (reel 2114) and the Henry E. 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Scott 210 1$aHook, England :$cWaterside Press,$d2016. 210 4$d©2016 215 $a1 online resource (290 pages) 311 $a1-909976-35-0 320 $aIncludes bibliographical references and index. 606 $aJudicial error 606 $aJudicial error$xPsychological aspects 608 $aElectronic books. 615 0$aJudicial error. 615 0$aJudicial error$xPsychological aspects. 676 $a345.0122 700 $aAnderson$b David C.$0903972 702 $aScott$b Nigel P. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910466105203321 996 $aThree false convictions, many lessons$92020856 997 $aUNINA LEADER 03816nam 2200517 450 001 9910483098703321 005 20220203170533.0 010 $a1-4842-7032-0 024 7 $a10.1007/978-1-4842-7032-5 035 $a(CKB)5590000000486867 035 $a(DE-He213)978-1-4842-7032-5 035 $a(MiAaPQ)EBC6640810 035 $a(Au-PeEL)EBL6640810 035 $a(OCoLC)1256627333 035 $a(CaSebORM)9781484270325 035 $a(EXLCZ)995590000000486867 100 $a20220203d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine learning for Oracle database professionals $edeploying model-driven applications and automation pipelines /$fHeli Helskyaho, Jean Yu, Kai Yu 205 $a1st ed. 2021. 210 1$a[Place of publication not identified] :$cAPress,$d[2021] 210 4$d©2021 215 $a1 online resource (XVI, 289 p. 156 illus.) 300 $aIncludes index. 311 $a1-4842-7031-2 327 $a1. Introduction to Machine Learning -- 2. Oracle and Machine Learning -- 3: Oracle Machine Learning for SQL -- 4. Oracle Autonomous Database for Machine Learning -- 5. Running Oracle Machine Learning with Autonomous Database -- 6. Building Machine Learning Models with OML Notebooks -- 7. Oracle Analytics Cloud -- 8. Delivery and Automation Pipeline in Machine Learning -- 9. ML Deployment Pipeline Using Oracle Machine Learning -- 10. Building Reproducible ML Pipelines Using Oracle Machine Learning. 330 $aDatabase developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle?s Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines. Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions. You will: Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation Understand Oracle offerings for machine learning Develop machine learning with Oracle database using the built-in machine learning packages Develop and deploy machine learning models using OML4SQL and OML4R Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning Develop and deploy machine learning projects in Oracle Autonomous Database Build an automated pipeline that can detect and handle changes in data/model performance. 606 $aMachine learning 606 $aDatabase management 615 0$aMachine learning. 615 0$aDatabase management. 676 $a005.7585 700 $aHelshyaho$b Heli$01082494 702 $aYu$b Kai 702 $aYu$b Jean 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483098703321 996 $aMachine learning for Oracle database professionals$92597982 997 $aUNINA